Precipitable water and CAPE dependence of rainfall intensities in China View Full Text


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Article Info

DATE

2019-03

AUTHORS

Wenhao Dong, Yanluan Lin, Jonathon S. Wright, Yuanyu Xie, Xungang Yin, Jianping Guo

ABSTRACT

The influence of temperature on precipitation in China is investigated from two aspects of the atmospheric water cycle: available water vapor and atmospheric instability. Daily observations are used to analyze how rainfall intensities and its spatial distribution in mainland China depend on these two aspects. The results show that rainfall intensities, and especially rainfall extremes, increase exponentially with available water vapor. The efficiency of water vapor conversion to rainfall is higher in northwestern China where water vapor is scarce than in southeastern China where water vapor is plentiful. The results also reveal a power law relationship between rainfall intensity and convective instability. The fraction of convective available potential energy (CAPE) converted to upward velocity is much larger over southeastern China than over the arid northwest. The sensitivities of precipitation to temperature-induced changes in available water vapor and atmospheric convection are thus geographically reciprocal. Specifically, while conversion of water vapor to rainfall is relatively less efficient in southeastern China, conversion of CAPE to upward kinetic energy is more efficient. By contrast, in northwestern China, water vapor is efficiently converted to rainfall but only a small fraction of CAPE is converted to upward motion. The detailed features of these relationships vary by location and season; however, the influences of atmospheric temperature on rainfall intensities and rainfall extremes are predominantly expressed through changes in available water vapor, with changes in convective instability playing a secondary role. More... »

PAGES

3357-3368

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s00382-018-4327-8

DOI

http://dx.doi.org/10.1007/s00382-018-4327-8

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1105208851


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